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The full training configuration is also fully transparant and can be found below.
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Hope this model will prove useful.
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There's GGUF versions available here: https://huggingface.co/CultriX/MergeTrix-7B-GGUF
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Kind regards,
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CultriX
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#
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MergeTrix-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [abideen/NexoNimbus-7B](https://huggingface.co/abideen/NexoNimbus-7B)
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The full training configuration is also fully transparant and can be found below.
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Hope this model will prove useful.
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There's GGUF versions available here for inference: https://huggingface.co/CultriX/MergeTrix-7B-GGUF
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Kind regards,
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CultriX
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# Shoutout
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Once again, a major thank you and shoutout to @mlabonne for his amazing article that I used to produce this result which can be found here: https://towardsdatascience.com/merge-large-language-models-with-mergekit-2118fb392b54
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My other model, CultriX/MistralTrix-v1, was based on another great article from the same guy, which can be found here: https://towardsdatascience.com/fine-tune-a-mistral-7b-model-with-direct-preference-optimization-708042745aac
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(I hope he doesn't mind me using his own articles to beat him on the LeaderBoards for the second time this week... Like last time, all credit should be directed at him really!)
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# MODEL INFORMATION:
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# NAME: MergeTrix-7B
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MergeTrix-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [abideen/NexoNimbus-7B](https://huggingface.co/abideen/NexoNimbus-7B)
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